In Multi User Multiple Input Multiple Output MIMO (MU-MIMO) systems, an extended version of space-division multiple access (SDMA) is employed in which a single transmitter sends separate signals to multiple receivers which then receive separate signals simultaneously over the same channel. In such systems, due to the spatial processing that occurs at the transmitters, it is necessary to have knowledge at the receiver of the channel characteristics for the different signals so that effective signal detection and decoding of the signals can take place. MIMO (including MU-MIMO) communication systems are employed by many different communication standards, such as IEEE 802.11n (Wi-Fi), Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) and Long Term Evolution Advanced (LTE-A), Worldwide Interoperability for Microwave Access (WiMAX) and High Speed Packet Access Evolution (HSPA+).
The three most relevant detector/decoding methods (known to the applicants) in MIMO based communication systems are:
ZF Detection (Zero Forcing)
The ZF detector inverts the channel and leads to full interference rejection, but this approach suffers from noise enhancement as the system noise is ignored in the detection process.
MMSE Detection (Minimum Mean Square Error)
The MMSE detector takes the channel and the noise into account and provides a solution, which minimizes the mean square error between estimated and transmitted data symbols.
ML Detection (Maximum Likelihood)
Unlike the ZF and the MMSE detector, the ML detector adopts a non-linear approach, which finds the most likely transmitted data symbols that cause the smallest squared error from the received data symbols by doing a joint detection via an exhaustive search, taking all possible received data symbol constellations into account. ML detection generally provides the best possible interference reduction of all available detection methods and no noise enhancement, resulting in the best possible decoding performance.
If the reference signals are known for the other user equipment (UE) (as is the case for TM8 and TM9 in LTE-A), then a ZF or MMSE decoder could be used to reduce the inter-UE interference for better demodulation performance. ML is even better, but ML requires knowledge of the modulation order of the other UE (as does MMSE-SIC), which in general is not known in LTE and certain other types of communication system.